The invention relates to gamma-ray spectrometry, and in particular to calibration sources for gamma-ray spectrometers and gamma-ray spectrometers having calibration sources.
Gamma-ray spectrometers are used in a wide variety of applications, for example to identify and monitor gamma-ray sources in scientific, industrial, and environmental monitoring applications, e.g. for security screening of personnel and cargo at border crossings, or to search generally for orphaned radioactive sources. A common class of gamma-ray spectrometers is based on organic (plastic) or inorganic (crystal) scintillator materials.
FIG. 1 shows an example of a conventional crystal scintillation spectrometer 2. The spectrometer is generally axially symmetric with a diameter of around 8 cm and a length of around 8 cm. The spectrometer 2 comprises a scintillation crystal 4 which scintillates when a gamma-ray is absorbed within it. A common scintillation crystal material is thallium doped sodium iodide (NaI(Tl)). There are, however, various other scintillator crystals, and also scintillator plastics, that may be used.
The scintillation crystal 4 is in a hermetically sealed body 6 with Al2O3 powder packing arranged around the crystal 4 to act as a reflective material. A glass entrance window 8 is situated on the upper end-face of the package. Gamma-rays from a source enter the spectrometer through the entrance window 8. Gamma-rays interact with the scintillation crystal 4 in scintillation events in which lower-energy photons are generated, e.g. optical photons. The scintillation crystal 4 is optically coupled to a photomultiplier tube (PMT) 10 for detecting photons generated in the scintillation crystal 4 in gamma-ray detection events. Thus the PMT 10 is operable to output a signal indicative S of the intensity of the scintillation flash generated in the crystal 6 in response to each gamma-ray interaction. The intensity of the flash depends on the amount of the energy of the incident gamma-ray deposited in the crystal.
Output signals S from the PMT 10 are routed to a spectrum analyser 12, e.g. a multi-channel analyser. The amplitudes of the respective output signals S are indicative of the energy of the corresponding incident gamma-rays deposited in the crystal. The relationship between an energy deposit D in the scintillation body 4 and an resulting output signal S is defined by a response function of the spectrometer.
The spectrum analyser 12 is operable to process the output signals received from the PMT in a given integration time (or in an accumulating manner) and to generate an energy loss spectrum for the corresponding detection events. This requires the spectrum analyser 12 to convert the measured output signals S to estimates of the energy deposited D in the gamma-ray detector in the corresponding events. The mapping from output signals S to energy deposit D is defined by a calibration function. The calibration function is selected to provide an inverse to the response function for the spectrometer. That is to say, if an energy deposit D0 in a crystal is converted to an output signal S0 in accordance with the spectrometer's response function, the aim of the calibration function is to invert the spectrometer's response so as to convert the output signal S0 back to an estimate of the energy deposit D0.
The general principles underlying the of application of calibration functions to in effect undo a gamma-ray spectrometer's response function are well known. The calibration function may, for example, be based on a look-up table, or a functional relationship that provides for a conversion of an observed signal amplitude S to an estimated energy deposit D. The calibration function may be based on empirical observations of calibration sources having known spectra, or theoretical predictions.
By way of an example of a spectrometer's response to an energy deposit, an energy loss of 1 MeV in a NaI(Tl) scintillator crystal such as shown in FIG. 1 might generate around nγ=38,000 photons. The Al2O3 powder surrounding the scintillator crystal provides for relatively high diffuse reflectance, typically providing a transfer efficiency T such that that perhaps 85% or so of generated photons are transferred to the photo-cathode of the PMT 10. The quantum-efficiency QE of a PMT at the wavelength of interest is typically around 25%. Thus the number of charge-carriers Ncc released from the photo-cathode of the PMT in response to the 1 MeV energy deposit will be around 8,000 (i.e. nγ*T*QE, where nγ=38,000, T=0.85, and QE=0.25). The output signal S from the PMT will thus be 8000G0 (in arbitrary units), where G0 is a measure of the gain of the PMT. Thus the calibration function here should ideally be defined such that an output signal of 8000G0 is mapped back to an energy loss of 1 MeV.
As noted above, the general principles underlying the application of calibration functions to gamma-ray spectrometer data are well understood. For example it is known that a spectrometer response function will generally be non-linear (i.e. a twice-as-high energy deposit D in the scintillation crystal will not in general correspond with a twice-as-high output signal S from the PMT). Some aspects of an arbitrary spectrometer response function are represented in Table 1. It will be appreciated, however, that this is purely a simple example for the purposes of explanation, it is not intended to reflect the true response characteristics of any particular scintillation spectrometer.
TABLE 1Energy deposit DPMT Output signal S(MeV)(arbitrary units)0.76230 * G00.86880 * G00.97470 * G01.08000 * G01.18470 * G01.28880 * G01.39230 * G0
The PMT output signals S shown in Table 1 is the product of two basic parameters, namely the number of charge carriers Ncc generated at the photo-cathode of the PMT (e.g. 8000 at 1 MeV), and the gain of the PMT (G0). As noted above, the spectrum analyser component of the gamma-ray spectrometer is operable to convert an observed PMT output signal S to an estimated energy deposit D in the crystal. This could be done by reference to a look-up table such as represented in Table 1, but more likely will be done by applying a functional parameterisation of the calibration. For example, the spectrometer response function represented in Table 1 may be parameterised asS=(11000*D−3000*D2)*G0  (Equation 1).
This equation may be solved for a given observed output signal S to provide an estimate of energy loss D.
A problem with scintillator-based gamma-ray spectrometers is that the number of charge carriers Ncc generated at the photo-cathode of a PMT for a given gamma-ray energy deposit in a given spectrometer is not necessarily constant. For example, the number of charge carriers Ncc depends relatively strongly on the temperature of the spectrometer (primarily because the number of photons nγ generated in the energy deposit depends on the temperature of the scintillation crystal). This means the spectrometer's response function can vary with changing conditions. As such any assumed calibration function for converting from output signal S to incident energy deposit D will only be correct for some conditions (i.e. the conditions for which the calibration function was originally determined). This is problematic because a failure to properly map output signals S back to energy deposits D will lead to a poorly calibrated spectrum, e.g. with peaks appearing at the wrong energies. The problem of a spectrometer's response changing according to different conditions arises to some extent in all gamma-ray spectrometers, and not just in scintillator-based spectrometers.
A known way of dealing with this problem is to adjust the gain of the acquisition system (e.g. of the PMT itself, or of an associated signal amplifier). This is generally known as stabilisation.
Stabilisation may, for example, be achieved by adjusting system gain in response to measured changes in environmental conditions so as to compensate for corresponding changes in the spectrometer's response. For example, suppose the response function represented in Table 1 was applicable for a spectrometer at 20° C., and there was known to be a 1% drop in Ncc for each 1° C. rise in temperature. This means at a temperature of 30° C., an energy deposit of 1 MeV would generate only around 7200 charge carriers (as opposed 8000 at 20° C.), and hence an output signal of S=7200*G0 would be seen. If no account were taken of the change in environmental conditions, this output signal would be mapped back to an estimated energy deposit of between 0.8 and 0.9 MeV, and so result in an inaccurate energy-loss spectrum. Thus it is known to monitor the temperature of a spectrometer and to compensate for changes in the number of charge carriers generated for a given energy deposit by applying a corrective temperature-dependent calibration factor f to the PMT gain. For example, if the temperature changed by an amount known to cause a 10% fall in charge carriers, the PMT gain could be increased by 11% to compensate. Thus for the 30° C. example give above, the output signal would become S=Ncc*f*G0=7200*1.11*G0=8000 G0. This would then be correctly mapped back to an energy deposit of 1 MeV by reference to the calibration function represented in Table 1. A problem with this approach is that it is difficult to monitor changes in environmental conditions, and to model their impact on a spectrometer's response, with high accuracy.
Another approach for providing stabilisation is based on monitoring the response of a spectrometer to a source of calibration gamma-rays of known energy(ies). A calibration factor f may then be applied to the PMT gain (or other data acquisition system gain), where f is selected such that output signals associated with calibration gamma-rays are correctly mapped back to the known energy of these calibration events. For example, a servo loop may be provided with the system gain being adjusted in response to apparent differences between the known energies for calibration events and the energies determined from their output signals S via the assumed calibration function. An advantage of this approach is that all changes in the spectrometer's response function can be accounted for simultaneously regardless of cause. However the approach must be performed separately from data acquisition from a target of interest, or requires a technique for distinguishing calibration events from “real” events so that the calibration events do not contaminate the energy loss spectrum determined for the real events.
Previously proposed schemes for calibration-source-based stabilisation have employed calibration isotopes (e.g. Co-60, Cs-137 or Na-22) to dope a small plastic secondary scintillation detector viewed by a separate PMT to provide an electronic gating signal each time that a beta-particle is detected in the plastic [1, 2]. Gamma-rays detected in a main detector at the same time as a beta-detection event in the secondary detector are taken to be associated with the calibration source, and hence of a known energy. These can be processed separately from other events and used to provide spectral stabilization. This approach results in relatively bulky spectrometers and is not practical for use in all situations, e.g. for use in compact hand-held gamma-ray spectrometers.
Another previously proposed scheme has used Na-22 as a calibration source between a primary spectrometer and a secondary gamma-ray detector. The approach relies on the fact that Na-22 emits a positron which promptly annihilates to produce a pair of 511 keV photons propagating in opposite directions. If one of the annihilation gamma-rays is detected in the secondary gamma-ray detector, this can be used to provides an electronic signal that can be used to label simultaneous events in the primary spectrometer as being associated with the Na-22 calibration source [3]. This again allows the calibration events to be separated from “real” events. The system gain can then be adjusted so the energies for the Na-22 emissions determined using the primary spectrometer match the known emission energies for this isotope, thereby simultaneously stabilizing the observed spectrum for the real events.
Another technique widely used in stabilizing the gain of gamma-ray spectrometers is based on the incorporation of a weak alpha-emitting source, e.g. Am-241, into the scintillation crystal assembly. The alpha-particles from the Am-241 then generate a large energy-deposit in the crystal which is beyond the energy-range of interest of most gamma-ray spectrometers (˜4 MeV). A servo-loop may then be set to maintain this peak at a constant position in the spectrum as temperature, and other environmental conditions, change. This helps ensure the gamma-ray spectrum recorded at the same time is stabilized [4]. However, in addition to emitting 4 MeV alpha particles, Am-241 also emits 59 keV gamma-ray emission. There is no way of identifying these events in an observed spectrum to separate them from “real” events in this energy region, that is to say, the calibration source contaminates the observed spectrum. This makes the approach unsuitable for many systems isotope identification systems which need to be able to reliably identify isotopes having emission lines in this energy region, including Am-241 itself.
There is therefore a need for improved calibration sources for use with gamma-ray spectrometers.